To start with, we align the total number of rays seen during training.
We add support of ray undistortion [1]} in the third-party implementation of NSFF [2]} to make sure that the training rays are the same across codebases.
All models are trained with view-dependency modeling turned on.
We did not find appearance encoding [3]} helpful in terms of quantitative results.
This might due to the lighting difference between training and validation captures – a common issue in evaluation discussed in mip-NeRF 360 [4]}.
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